Research Interests: Database, data mining
Office Phone: 86-10-6276 5825
GAO, Jun is a professor in the Department of Computer Science and technology, School of EECS. He obtained his B.Sc. from Shandong University in 1997, and Ph.D. from Peking University in 2003 respectively. His research interests include distributed data management, big graph management and mining.
Dr. Gao has published more than 30 research papers, and most of them are published in top-tier conferences and journals, such as SIGMOD, VLDB, TKDE, and VLDBJ. He has served in the Technical Program Committee of various international conferences including ICDE, CIKM, PAKDD, WAIM.
Dr. Gao has more than ten research projects including NSFC, 863 programs, etc. His research achievements are summarized as follows:
1) Frameworks of Distributed Graph Processing: These frameworks abstract and support the common routines of various graph computing algorithms. He proposed method to leverage existing infrastructures, like the relational database, MapReduce for graph computing. He devised a message online computing model to lower the memory burden in Pregel-like frameworks. He also designed a hybrid evaluation model to combine the advantages of synchronous and asynchronous methods.
2) Processing and Mining on Large Graphs. Various graph processing and mining methods are needed in applications. He designed an efficient top-k shortest path discovery method in large graphs, and introduced a distributed graph pattern matching algorithm to achieve high efficiency in billion edges graph. He also proposed a SimRank computational method based on the unidirectional random walk, which achieves high efficiency without needing the indexing overheads. His team designed graph based recommendation systems, and deployed them in real-life applications.